source: trunk/GDEHELP/HELP_WRITTEN/raxml.help

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1RAxML
2
3DESCRIPTION
4
5        RAxML (Randomized Axelerated Maximum Likelihood) is a program for sequential and parallel Maximum
6        Likelihood-based inference of large phylogenetic trees.
7
8        It has originally been derived from fastDNAml which
9        in turn was derived from Joe Felsenteins dnaml which is part of the PHYLIP package.
10
11        Author: Alexandros Stamatakis
12
13                Ecole Polytechnique Federale de Lausanne
14                School of Computer & Communication Sciences
15                Laboratory for Computational Biology and Bioinformatics (LCBB)
16
17                Alexandros.Stamatakis@epfl.ch
18
19        Original documentation can be found at
20        http://icwww.epfl.ch/~stamatak/index-Dateien/countManual7.0.0.php
21
22        Several parts of this documentation have been used here.
23
24        Version distributed with ARB and used by this window: RAxML 7.0.3
25
26PARAMETERS
27
28        Here we only describe the parameters adjustable via the ARB interface.
29
30        Weighting mask
31
32                Specify a weighting mask for the alignment. This increases penalty for
33                mismatches in conservative regions and decreases it in variable regions of
34                the alignment.
35
36                Since RAxML only accepts natural numbers as weights, ARB has to multiply
37                the weights of e.g. POS_VAR_BY_PARSIMONY, such that the smallest weight
38                equals 1.
39
40                As a consequence the likelihood of the calculated tree is ~ 100000 times higher
41                than w/o weighting mask.
42
43        Base tree / Use as constraint tree / Generate random starting tree
44
45                Specifying a base tree works different depending on several other parameters.
46
47                Generally there are four different possibilities:
48
49                        - If you don't select a base tree (i.e. select '????') RAxML generates
50                          a starting tree using a Maximum Parsimony algorithm
51
52                        - If you additionally set 'Generate random starting tree' to 'Yes'
53                          RAxML generates a completely random starting tree.
54                          On smaller datasets (around
55                          100-200 taxa) it has been observed that this might sometimes yield
56                          topologies of distinct local likelihood maxima which better
57                          correspond to empirical expectations.
58
59                        - If you select a base tree, RAxML adds all species which are marked but
60                          are not in tree to this base tree using Maximum Parsimony.
61                          The resulting tree is then optimized using the selected RAxML algorithm.
62
63                        - If you set 'Use as constraint tree' to 'Yes' the topology of the given
64                          base tree will not be changed, only the position of the added species
65                          will be rearranged.
66
67                Notes:
68
69                        - All species contained in the 'Base tree' have to marked - otherwise
70                          RAxML will stop with an error.
71
72        Nucleotide Substitution Model / Rate Distribution Model / AA Substitution Model
73
74                Please refer to the original documentation for details on Substitution Models
75
76        Number of rate categories (DNA GTRCAT only)
77
78                This option allows you to specify the number of distinct rate categories,
79                into which the individually optimized rates for each individual site are ?thrown?
80                (Default = 25)
81
82        Optimize branches/parameters
83
84                Specifies that RAxML shall optimize branches and model parameters on
85                bootstrapped trees as well as print out the optimized likelihood. Note,
86                that this option only makes sense when used with the GTRMIX or
87                GTRGAMMA models (or the respective AA models)!
88
89        RAxML algorithm
90
91                new rapid hill climbing
92
93                        RAxML will execute the new (as of version 2.2.1) and significantly
94                        faster rapid hill-climbing algorithm
95
96                old hill climbing
97
98                        RAxML will execute the slower old search algorithm of version 2.1.3,
99                        this is essentially just for backward compatibility.
100
101                optimize input tree
102
103                        RAxML will optimize the model parameters and branch lengths of the
104                        selected 'Base tree' under GTRGAMMA
105
106                rapid bootstrap analysis
107
108                        tell RAxML to conduct a rapid Bootstrap analysis and search for the
109                        best-scoring ML tree in one single program run.
110
111                        Uses the seed specified at 'Random seed'
112
113                advanced bootstrap + refinement of BS tree
114
115                        performs a really thorough standard bootstrap. RAxML will refine the
116                        final BS tree under GAMMA and a more exhaustive algorithm.
117
118                add new sequences to input tree (MP)
119
120                        performs just pure stepwise MP addition of new sequences
121                        to an incomplete starting tree.
122
123                        You have to mark all species in tree AND all species which should be
124                        added to the tree.
125
126                        Note: RAxML has a bug in the tree-reader and rejects many
127                        trees as unrooted/multifurcated.
128                        You can to use 'Tree/Beautify Tree' and select the lowest
129                        mode (short branches first) as a workaround.
130
131                randomized tree searches (fixed start tree)
132
133                        will perform several randomized tree searches (as specified at
134                        'Number of runs'), that always start from one fixed starting tree.
135
136        Random seed
137
138                Used as random seed for 'rapid bootstrap analysis'
139
140        Initial rearrangement setting
141
142                This allows you to specify an initial rearrangement setting for the initial
143                phase of the search algorithm. If you specify e.g. 10 the pruned subtrees will
144                be inserted up to a distance of 10 nodes away from their original pruning point.
145
146                If you don’t specify anything here, a "good" initial rearrangement setting
147                will automatically be determined by RAxML.
148
149        Number of runs
150
151                Enter a number > 1 to run the selected algorithm multiple times.
152                Specifying e.g. '10' will result in 10 generated trees.
153
154        Select ## best trees
155
156                If 'Number of runs' is > 1, this specifies how many of the generated tree
157                shall be imported or merge using consense.
158
159                The trees with the best likelihood will be selected.
160
161        What to do with selected trees?
162
163                Import into ARB
164
165                        All selected trees will be imported into ARB
166
167                Create consense tree
168
169                        Calls consense on all selected trees and imports
170                        the resulting consense tree into ARB.
171
172
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